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Summary
| Description |
English: From Data to Knowledge - 508 - Una-May O'Reilly
Slides: http://lyra.berkeley.edu/CDIConf/pdfs... Una-May O'Reilly: "Knit: Integrating Large Scale Partial Cognitive Analyses of Data". A video from the UC Berkeley Conference: From Data to Knowledge: Machine-Learning with Real-time and Streaming Applications (May 7-11, 2012). Abstract Una-May O'Reilly (MIT, CSAIL) Increasingly humans are becoming an integral part of knowledge discovery systems. Their ability to process information based on the context and their perception allows them to discern unique and novel patterns. However these systems are vulnerable to noisy and inconsistent behavior of humans.Additionally they are limited by human's cognitive capacity in processing data in real time. Our goal is to develop real-time knowledge discovery techniques which extend/accelerate/amplify the value of analyst's locally discerned patterns. Our approach knits together local similarity sets without explicit features. It also actively presents data to different analysts to effectively derive a consensus of global similarity. |
| Date | |
| Source | From Data to Knowledge - 508 - Una-May O'Reilly at 0:36, cropped, brightened |
| Author | ckleinastro |
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From Data to Knowledge - 508 - Una-May O'Reilly at 0:36, cropped, brightened, was reviewed on 14 September 2020 by reviewer Leoboudv, who confirmed that it was available there under the stated license on that date.
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 13:49, 14 September 2020 | | 499 × 520 (59 KB) | GRuban | {{Information |description={{en|1=From Data to Knowledge - 508 - Una-May O'Reilly Slides: http://lyra.berkeley.edu/CDIConf/pdfs... Una-May O'Reilly: "Knit: Integrating Large Scale Partial Cognitive Analyses of Data". A video from the UC Berkeley Conference: From Data to Knowledge: Machine-Learning with Real-time and Streaming Applications (May 7-11, 2012). Abstract Una-May O'Reilly (MIT, CSAIL) Increasingly humans are becoming an integral part of knowledge discovery systems. Their ability... |
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